Kim W Last | PubMed Health

PubMed2003

Presentation serum selenium predicts for overall survival, dose delivery, and first treatment response in aggressive non-Hodgkin's lymphoma.

PURPOSE: This study was undertaken to test the hypothesis that serum selenium concentration at presentation correlates with dose delivery, first treatment response, and overall survival in patients with aggressive B-cell non-Hodgkin's lymphoma. PATIENTS AND METHODS: The patients presented between July 1986 and March 1999 and received anthracycline-based chemotherapy, radiotherapy, or both. The total selenium content was retrospectively analyzed in 100 sera, frozen at presentation, using inductively coupled plasma mass spectrometry. RESULTS: The serum selenium concentration ranged from 0.33 to 1.51 micromol/L (mean, 0.92 micromol/L; United Kingdom adult reference range, 1.07 to 1.88 micromol/L). Serum selenium concentration correlated closely with performance status but with no other clinical variable. Multivariate analysis revealed that increased dose delivery, summarized by an area under the curve, correlated positively with younger age (P <.001), advanced stage (P =.001), and higher serum selenium concentration (P =.032). Selenium level also correlated positively with response (odds ratio, 0.62; 95% confidence interval [CI], 0.43 to 0.90; P =.011) and achievement of long-term remission after first treatment (log-rank test, 4.38; P =.036). On multivariate analysis, selenium concentration was positively predictive of overall survival (hazard ratio [HR], 0.76 for 0.2 micromol/L increase; 95% CI, 0.60 to 0.95; P =.018), whereas age indicated negative borderline significance (HR, 1.09; 95% CI, 0.99 to 1.18; P =.066). CONCLUSION: Serum selenium concentration at presentation is a prognostic factor, predicting positively for dose delivery, treatment response, and long-term survival in aggressive non-Hodgkin's lymphoma. Unlike most existing prognostic factors in aggressive non-Hodgkin's lymphoma, selenium supplementation may offer a novel therapeutic strategy in this frequently curable malignancy.

Adult↗

PubMed2002

Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning.

Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is curable in less than 50% of patients. Prognostic models based on pre-treatment characteristics, such as the International Prognostic Index (IPI), are currently used to predict outcome in DLBCL. However, clinical outcome models identify neither the molecular basis of clinical heterogeneity, nor specific therapeutic targets. We analyzed the expression of 6,817 genes in diagnostic tumor specimens from DLBCL patients who received cyclophosphamide, adriamycin, vincristine and prednisone (CHOP)-based chemotherapy, and applied a supervised learning prediction method to identify cured versus fatal or refractory disease. The algorithm classified two categories of patients with very different five-year overall survival rates (70% versus 12%). The model also effectively delineated patients within specific IPI risk categories who were likely to be cured or to die of their disease. Genes implicated in DLBCL outcome included some that regulate responses to B-cell-receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis. Our data indicate that supervised learning classification techniques can predict outcome in DLBCL and identify rational targets for intervention.

Antineoplastic Combined Chemotherapy Protocols↗